Supply chain experts, smart manufacturing engineers, data and applications architects, and manufacturing business consultants share best practices for using smart manufacturing and supply chain solutions.
CESMII just named Toward Zero the Smart Manufacturing Innovation Award winner for its groundbreaking achievement in collecting smart manufacturing data from CNC machines. During an interview with Aaron Muhl, founder and president of the smart manufacturing engineering firm, I learned more about the award and the innovations that led to CESMII honoring the Toward Zero team.
As companies continue to prepare for digital transformation, the debate around which data protocol is better for smart manufacturing systems rages on. The need to capture data from HAAS machines and other manufacturing equipment is a critical component because much of the data required for smart manufacturing originates in your company’s machines, robots, processing equipment, and inspection equipment. In some cases, the data resides in a computer on board the equipment; in many cases, the data sits in a proprietary controller. These data sources use a wide variety of protocols. Many standards organizations have attempted to consolidate communication protocols. A few leaders have emerged, but that perhaps has made decisions about how to capture machine data for smart manufacturing even more complex.
Data, particularly machine data, is a foundational component of every smart factory or OEE initiative. It fuels analytics, triggers actions ahead of problems or shutdowns, and provides insight for continuous improvement. Many companies start the smart factory journey with an automated OEE system because it’s a natural progression with a set of metrics they’re already familiar with. Despite advances in automated data collection and production analytics, a lot of manufacturing executives are still at odds about exactly which machine data is required to calculate OEE. Unfortunately, a lot of projects get sidetracked early on as stakeholders try to utilize every piece of machine-generated data from the multitude available. A more pragmatic approach is to apply machine data based on priorities around business goals. To that end, capturing the machine data required for OEE is a critical early activity for most smart factory initiatives.
Manufacturers serious about improving OEE need to invest in automated data collection. Though the intention of manual data collection is good, this approach doesn’t provide real-time insight or the level of accuracy and detail that an automated data collection can produce. Perhaps more importantly, automated data collection helps you shift employees’ attention to high-value work like running machines and solving problems that hinder operational performance.
Legacy factory equipment (manufacturing machines with no built-in data collection mechanism) presents a significant challenge when it comes to manufacturing data, particularly for companies that want to calculate OEE. That most basic of all manufacturing metrics isn’t the only reason manufacturing companies are eager to make older equipment IoT-compatible. Capturing the right data can transform manufacturing operations: it eases the disconnect between the factory and business processes, eliminates the lag time for management to access, analyze, and act on data, and resolves problems with planning, inventory control, the supply chain, and meeting customer expectations.
CESMII just named Toward Zero the Smart Manufacturing Innovation Award winner for its groundbreaking achievement in collecting smart manufacturing data from CNC machines. During an interview with Aaron Muhl, founder and president of the smart manufacturing engineering firm, I learned more about the award and the innovations that led to CESMII honoring the Toward Zero team.
As companies continue to prepare for digital transformation, the debate around which data protocol is better for smart manufacturing systems rages on. The need to capture data from HAAS machines and other manufacturing equipment is a critical component because much of the data required for smart manufacturing originates in your company’s machines, robots, processing equipment, and inspection equipment. In some cases, the data resides in a computer on board the equipment; in many cases, the data sits in a proprietary controller. These data sources use a wide variety of protocols. Many standards organizations have attempted to consolidate communication protocols. A few leaders have emerged, but that perhaps has made decisions about how to capture machine data for smart manufacturing even more complex.
Data, particularly machine data, is a foundational component of every smart factory or OEE initiative. It fuels analytics, triggers actions ahead of problems or shutdowns, and provides insight for continuous improvement. Many companies start the smart factory journey with an automated OEE system because it’s a natural progression with a set of metrics they’re already familiar with. Despite advances in automated data collection and production analytics, a lot of manufacturing executives are still at odds about exactly which machine data is required to calculate OEE. Unfortunately, a lot of projects get sidetracked early on as stakeholders try to utilize every piece of machine-generated data from the multitude available. A more pragmatic approach is to apply machine data based on priorities around business goals. To that end, capturing the machine data required for OEE is a critical early activity for most smart factory initiatives.
Manufacturers serious about improving OEE need to invest in automated data collection. Though the intention of manual data collection is good, this approach doesn’t provide real-time insight or the level of accuracy and detail that an automated data collection can produce. Perhaps more importantly, automated data collection helps you shift employees’ attention to high-value work like running machines and solving problems that hinder operational performance.
Legacy factory equipment (manufacturing machines with no built-in data collection mechanism) presents a significant challenge when it comes to manufacturing data, particularly for companies that want to calculate OEE. That most basic of all manufacturing metrics isn’t the only reason manufacturing companies are eager to make older equipment IoT-compatible. Capturing the right data can transform manufacturing operations: it eases the disconnect between the factory and business processes, eliminates the lag time for management to access, analyze, and act on data, and resolves problems with planning, inventory control, the supply chain, and meeting customer expectations.